Leland Hyman
Senior Machine Learning Scientist at Sherlock Biosciences
Greater Madison Area United States
Summary
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Senior🎓
Top SchoolLeland Hyman is a Senior Machine Learning Scientist with a decade of experience applying ML, heuristic optimization, and thermodynamic modeling to molecular diagnostics and protein engineering. He holds a Ph.D. in Cellular and Molecular Biology with a Computer Science minor from UW–Madison and has moved research into product at Sherlock Biosciences, advancing assay design with production-ready models and tooling. Leland combines deep learning and transfer learning on protein sequence tasks with hands-on full-stack development—he built and deployed a public diagnostic design web app used for low-resource disease testing. He has a track record of inventorship and translation, including a patent-pending single-cell technology and multiple peer-reviewed publications and grants. Comfortable at the intersection of science, engineering, and business, he has led consulting teams to evaluate market potential and advised investors on therapeutic opportunities. Colleagues describe him as an inventive problem solver who bridges wet-lab intuition and scalable ML systems to accelerate diagnostic and enzyme innovation.
10 years of coding experience
9 years of employment as a software developer
Ph.D., Cellular and Molecular Biology, 3.65, Ph.D., Cellular and Molecular Biology, 3.65 at University of Wisconsin-MadisonGithub contributions (5)
lbhyman/snp-lamp-design
Apr 2021 - May 2022
Contributions:1 release, 20 commits, 17 pushes in 1 year 1 month
lbhyman/snp-lamp-design-serverless
Jun 2021 - Sep 2021
Contributions:9 pushes, 3 branches in 3 months
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